AML - Data Scientist at Optimal Growth Technologies

Role Purpose

• We are seeking a highly analytical and commercially minded Specialist Data Scientist to drive the development of advanced analytics, machine learning, and AI-driven solutions that deliver business value and enhance customer experience.
• This role will focus on leveraging big data to build personalised, contextual, and intelligent solutions across consumer, merchant, financial services, and digital product portfolios.
• The successful candidate will work cross-functionally with commercial, engineering, data, and technology teams to develop predictive models, automate insights, and support strategic decision-making.

Key Responsibilities

• Develop Machine Learning and AI solutions that generate actionable business insights and drive personalisation.
• Build predictive models using large, complex, and diverse datasets.
• Develop and deploy machine learning models across various business domains.
• Write prototype and production-level code (e.g., PySpark) for automated model training and scoring.
• Track, monitor, and report on machine learning model performance.
• Use data visualisation techniques to communicate insights effectively and support data-driven storytelling.
• Collaborate with Data Engineering teams to support data ingestion and model productionisation.
• Work closely with stakeholders to deliver analytics solutions aligned to business objectives.
• Manage and take ownership of a portfolio of data science initiatives from development through to stakeholder engagement.
• Contribute to broader AI and Machine Learning capability development within the organisation.

Core Competencies & Experience

• Minimum 3+ years experience in Data Science or Statistical Modelling.
• Strong experience analysing and manipulating large, complex datasets.
• Proven ability to build and deploy predictive models (e.g., Churn, AML, Credit Risk, Fraud).
• Strong data visualisation skills with ability to present insights clearly.
• Commercial understanding of how AI & ML drive business value.
• Strong stakeholder management and communication skills.
• Ability to work effectively in a fast-paced environment.
• Analytical mindset with strong problem-solving capability.

Technical & Professional Requirements

• Bachelors or Masters Degree in Mathematics, Statistics, Economics, Computer Science, Engineering, Artificial Intelligence, or related quantitative field (essential).
• Professional or academic experience in Big Data analytics and deployment of models in real-world environments.
• Proficiency in Python or R.
• Experience with SQL, Spark, SAS or similar large dataset technologies.
• Experience with machine learning libraries such as H2O, scikit-learn, PyTorch.
• Experience with modelling techniques including:
• Random Forest
• Gradient Boosting
• K-means Segmentation
• Regression Analysis
• Factor Analysis
• Time-Series Forecasting
• Familiarity with visualisation tools such as Tableau, Qlik, or Power BI.